code: def predict_preamble(train_x_df, train_y_df):
      """Load the trained model and prepare a data point for prediction."""
      x = list(train_x_df.columns.values)
      model = build_model(len(x))
  
      try:
          model.load_weights(checkpoint_path)
      except errors.InvalidArgumentError:
          print("Weights couldn't be found, training before predicting")
          train(train_x_df, train_y_df)
          model = build_model(len(x))
  
      x = read_one_row(predict_row, train_x_df)
  
      return model, x
  
file_path: tf-encrypted/examples/application/house-credit-default/main.py
imports: import argparse
  import os
  import time
  import tensorflow
  import tf2onnx
  from tensorflow import keras
  from tensorflow.keras import layers
  from tensorflow.python import errors_impl
  from utils import data_prep
  from utils import read_one_row
label_desc: Use image node_id 5 for calling a global function with example usage: predict_preamble(train_x_df, train_y_df) and returns: model,  x